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Foundations of Statistics and Probability for Machine Learning
Janani Ravi
Janani Ravi
This course will teach you the concepts, theory, and implementation of basic statistics, probability, hypothesis testing, and regression analysis required to build and interpret meaningful machine learning models.
Read more
This course will teach you the concepts, theory, and implementation of basic statistics, probability, hypothesis testing, and regression analysis required to build and interpret meaningful machine learning models.
Read more
This course will teach you the concepts, theory, and implementation of basic statistics, probability, hypothesis testing, and regression analysis required to build and interpret meaningful machine learning models.
Learning the importance of p-values and test statistics and how these can be used to accept or reject the null hypothesis can lead you to explore the different types of t-tests and learn to choose the right one for your use case.
In this course, Foundations of Statistics and Probability for Machine Learning, you will learn to leverage statistics for exploratory data analysis and hypothesis testing.
First, you will explore measures of central tendency and dispersion including mean, mode, median, range, and standard deviation.
Then, you will explore the basics of probability and probability distributions and learn how skewness and kurtosis can give you important insights into your data.
Next, you will discover how you can perform hypothesis testing and interpret the results of these statistical tests.
Finally, you will learn how to perform and interpret regression models both simple regression with a single predictor and multiple regression with multiple predictors, and you will evaluate your regression models using R-squared and adjusted R-squared and understand the t-statistic and p-value associated with regression coefficients.
When you are finished with this course, you will have the skills and knowledge of statistics and data analysis needed to effectively explore and interpret your data as a precursor to applying machine learning techniques.
Register for this course and see more details by visiting:
OpenCourser.com/course/7myibh/foundations
What's inside
Syllabus
Course Overview
Understanding Descriptive Statistics and Probability Distributions
Interpreting Data Using Statistical Test
Performing Regression Analysis
Read more
Syllabus
Course Overview
Understanding Descriptive Statistics and Probability Distributions
Interpreting Data Using Statistical Test
Performing Regression Analysis
Read more
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for beginners interested in theoretical underpinnings of statistical techniques in machine learning
Assumes a foundational understanding of statistics and probability
Covers basic statistical concepts, making it useful for those without extensive prior knowledge
Course taught by instructors who have expertise in statistics applied to machine learning
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Career center
Learners who complete Foundations of Statistics and Probability for Machine Learning will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist is someone who uses data to solve problems. They use a variety of statistical and analytical tools to uncover insights from data and make predictions about the future. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Data Scientist by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively explore and interpret data, build machine learning models, and make informed decisions.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is someone who builds and deploys machine learning models. They use a variety of statistical and analytical techniques to train and test models to solve real-world problems. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Machine Learning Engineer by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively build and deploy machine learning models.
Statistician
Statistician
A Statistician is someone who uses statistics to design and conduct surveys, experiments, and other studies. They use a variety of statistical and analytical techniques to collect, analyze, and interpret data. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Statistician by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively design and conduct studies, collect, analyze, and interpret data, and communicate your findings.
Data Analyst
Data Analyst
A Data Analyst is someone who uses data to identify trends and patterns. They use a variety of statistical and analytical tools to explore data and uncover insights. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Data Analyst by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively explore and interpret data, identify trends and patterns, and communicate your findings.
Actuary
Actuary
An Actuary is someone who uses mathematical and statistical techniques to assess risk and uncertainty. They use these techniques to develop insurance policies and other financial products. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for an Actuary by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively assess risk and uncertainty, and develop insurance policies and other financial products.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst is someone who uses mathematical and statistical models to analyze financial data. They use these models to make investment decisions and develop trading strategies. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Quantitative Analyst by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively analyze financial data, make investment decisions, and develop trading strategies.
Biostatistician
Biostatistician
A Biostatistician is someone who uses statistical methods to design and analyze studies in the field of biology. They use these methods to investigate the causes and risk factors for diseases, and to develop new treatments and cures. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Biostatistician by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively design and analyze studies in the field of biology, investigate the causes and risk factors for diseases, and develop new treatments and cures.
Epidemiologist
Epidemiologist
An Epidemiologist is someone who studies the distribution and determinants of health-related states or events in specified populations. They use a variety of statistical and analytical techniques to investigate the causes of disease and other health problems, and to develop strategies to prevent and control these problems. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for an Epidemiologist by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively investigate the causes of disease and other health problems, and develop strategies to prevent and control these problems.
Market Researcher
Market Researcher
A Market Researcher is someone who studies the market for a particular product or service. They use a variety of statistical and analytical techniques to collect and analyze data about consumer behavior. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Market Researcher by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively collect and analyze data about consumer behavior, identify trends and patterns, and make recommendations to your clients.
Data Architect
Data Architect
A Data Architect is someone who designs and builds data systems. They use a variety of statistical and analytical techniques to ensure that data is accurate, reliable, and accessible. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Data Architect by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively design and build data systems, ensure that data is accurate, reliable, and accessible, and meet the needs of your organization.
Financial Analyst
Financial Analyst
A Financial Analyst is someone who analyzes financial data to make investment recommendations. They use a variety of statistical and analytical techniques to assess the risk and return of different investments. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Financial Analyst by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively analyze financial data, assess the risk and return of different investments, and make investment recommendations.
Business Analyst
Business Analyst
A Business Analyst is someone who analyzes business processes and systems to identify areas for improvement. They use a variety of statistical and analytical techniques to collect and analyze data, and to make recommendations for change. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Business Analyst by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively collect and analyze data, identify areas for improvement, and make recommendations for change.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst is someone who uses mathematical and statistical techniques to solve problems related to the operations of an organization. They use these techniques to improve efficiency, productivity, and profitability. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for an Operations Research Analyst by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively solve problems related to the operations of an organization, improve efficiency, productivity, and profitability.
Risk Manager
Risk Manager
A Risk Manager is someone who identifies and manages risks for an organization. They use a variety of statistical and analytical techniques to assess the likelihood and impact of different risks, and to develop strategies to mitigate these risks. The Foundations of Statistics and Probability for Machine Learning course provides a strong foundation for a Risk Manager by teaching you the basic concepts of statistics, probability, hypothesis testing, and regression analysis. This course will help you develop the skills you need to effectively identify and manage risks for an organization.
Teacher
Teacher
A Teacher is someone who teaches students at a school or other educational institution. They use a variety of teaching methods to help students learn new concepts and skills. The Foundations of Statistics and Probability for Machine Learning course may be useful for a Teacher who wants to teach statistics or probability at a high school or college level. This course will help you develop the skills you need to effectively teach statistics and probability, and to help your students learn these important concepts.
For more career information including salaries, visit:
OpenCourser.com/course/7myibh/foundations
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Foundations of Statistics and Probability for Machine Learning.
Provides a comprehensive introduction to statistical learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive introduction to statistical methods for machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive introduction to machine learning from a probabilistic perspective. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive introduction to reinforcement learning. It covers a wide range of topics, including Markov decision processes, value iteration, and policy iteration.
Save
Provides a thorough introduction to probability and statistics, with a focus on applications in data science. It is well-written and has many useful examples and exercises.
Provides a comprehensive introduction to probability and statistics for computer scientists. It covers a wide range of topics, including probability theory, statistical inference, and machine learning.
Provides a practical introduction to machine learning with Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Save
Provides a comprehensive introduction to deep learning. It covers a wide range of topics, including convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Provides a practical introduction to statistics and probability for engineers. It covers a wide range of topics, including descriptive statistics, inferential statistics, and regression analysis.
Save
Provides a readable introduction to probability and statistics. It consists of many examples and exercises.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/7myibh/foundations
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Time
133 hours
Level
Introductory
Via
Pluralsight
Instructor
Janani Ravi
Language
English
Good to know
Suitable for beginners interested in theoretical underpinnings of statistical techniques in machine learning
Assumes a foundational understanding of statistics and probability
Covers basic statistical concepts, making it useful for those without extensive prior knowledge
Course taught by instructors who have expertise in statistics applied to machine learning
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